Devesh Singh

DZNE is an interdisciplinary research institution that investigates neurodegenerative diseases. I am working towards creating applied explainable deep learning models to assist clinicians in detecting Alzheimer’s Disease from brain MRI scans.

Fellow of the Data Science for Social Good (DSSG) 2022 at TU Kaiserslautern, a full-time summer program training data scientists for social impact projects. In a team of 5, I worked with Paraguay's national procurement agency (DNCP) on detecting fraud in public procurement. My contributions included feature extraction, modeling, and pipeline building. Our team's solution improved fraud detection four-fold over DNCP’s current methods.

Research Questions: 1) How efficient are the image-to-image translation techniques which use deep generative networks, at bridging the gap between the synthetic and real domain datasets? 2) How effective is the overall synthetic data generation pipeline? Tasks: - Setting up and testing a pipeline for synthetic data generation - Using generative deep learning models: CycleGANs and CUT, for an image translation (computer vision) task Grade: 1.4

- Exploratory Data Analysis. - Modeling and forecasting inverter failure risks, using time series analysis. - Updating legacy Python repositories. - Code integration according to the Git-flow principles with Azure DevOps.

- Statistical testing of damage correlation to the usage. - Time series analysis of the machine signals. - Assisting the data collection and management process. - Analyze, visualize and infer knowledge from many different data sources.

Built explainable models, from a bio-medical data set to model tinnitus distress. Data Cleaning and Visualization, Exploratory Analysis, and Feature Selection were some of the steps involved in the process.

- Underwent a technical training in DotNet desktop and web application development. - Developed a holistic understanding of the financial system.

Grade: 1.3 Machine Learning | Deep Learning | Generative Modeling | Information Retrieval | Data Mining | Business Analytics | Database Management | Recommender Systems | Heuristic Optimization

Grade: 7.35/10 Software Engineering | Database Management | Computer Networks | OOPs (Java, C++) | Probabilistic Processes